Autonomous Mobility

Which sensor to pick to achieve full autonomy?

By Ket Teris - Jul 12 2018
As the trend move towards full autonomy of vehicles, the companies are emphasizing more and more on the high efficiency and reliability of sensors. Companies are weighing more on the cost optimized sensor technology that will attain high safety levels. Till today, camera was the dominant sensor, highly preferred by carmakers and tier-1 suppliers for developing ADAS and level-2 vehicles. Radar has also been used in the automotive industry from decades. However, to achieve the high level autonomy (level-3 and higher), camera or radar alone does not create sufficient data and hence the mix of camera, radar and LiDAR is being emphasized by most of the stakeholders in the autonomous vehicle industry.

Every sensor has its advantages and limitations; hence, the major question arises –which sensor to pick to achieve full autonomy?

VP Marketing, Leading Tier 1 Automotive Supplier

Radar can determine the distance between the vehicle and objects in the way, non-susceptible to environmental conditions, can calculate the velocity and angle of the object and can be effective for applications such as ACC and AEBS. However, the sensor has limitations in detecting thin objects or vehicles such as bicycles and motorcycles. Also, the sensor might not react correctly to certain situations on the road due to low resolution. On the other hand, cameras can perfectly distinguish between the objects and offers good resolution with color and contrast picture capturing. The sensor is dominating the industry in terms of volume; however, the massive amount of data gathered by this sensor makes the data processing task extremely complex.

The penetration of LiDAR in automotive industry has attracted many carmakers, and today, the sensor is considered as most reliable and highly precise option. LiDAR provides 360 degree 3D view with good resolution, can detect and classify objects, offers good range, very less-susceptible to environmental situations, including many other advantages. Though camera can identify objects, and radars can calculate the distance and angle of the obstacle, LiDAR can achieve both with high precision. This is the reason, major stakeholders in the autonomous driving space are seen to be inclined more towards LiDAR development and deployment.

High cost is the major drawback of this sensor, other limitation such as large size and resolution can be eliminated with the strong R&D in the field. Companies are working on different LiDAR technologies to overcome the limitations. Also, the mass production could lead in to the cost reduction, which would make LiDAR as ideal sensor for high level autonomy. Market leaders are looking towards this sensor as a game changer and have started focusing on its development at greater pace.

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